Moderated by Emily, Digital Transformation Consultant at Hyperbots.
Emily: Alright. Hello, everyone! This is Emily, and I am a digital transformation consultant at Hyperbots. Today we are joined by John Silverstein, and we’ll be talking about strategies for matching in accounts payable. John is the VP of FPNA at Extreme Reach and has over 20 years of experience navigating Fortune 500 giants and dynamic startups. Let’s dive right into the topic, John. Just to start with a very easy question: What is the choice of fields for matching in the accounts payable process, and why is it critical for any organization?
John Silverstein: This is one of the most important parts of the AP process. Once you set up the matching criteria, it controls whether your matching is efficient and accurate and whether you’ll need to perform rework. Essentially, it ensures that we pay for what we purchase. Proper matching can prevent errors, fraud, and overpayments while ensuring compliance with contracts and internal policies. However, being too strict on the matching can slow down processes. It’s not just about the matching itself; it’s also about what data you’re gathering. You might match on three or four fields, but you could be gathering 20 fields, which may not need exact matches but can help inform decisions down the line.
Emily: Got it. So, John, can you explain the difference between two-way and three-way matching and when each is most appropriate?
John Silverstein: Two-way matching doesn’t involve the receipt of goods; it’s based only on matching the invoice with the PO. This method speeds up the process since you’re matching PO fields against the invoice fields. It’s especially useful for services or low-value transactions where you don’t necessarily have goods to receive. Three-way matching, on the other hand, includes the receipt of goods. This ensures that what you ordered on the PO is what was received. This method is more thorough and is ideal for high-value or high-risk items.
Emily: In your experience, what are the most critical fields to include in three-way matching, and why?
John Silverstein: The most critical fields are the PO number, quantity, unit price, and total amount. These fields ensure that you’ve received everything as expected and that the invoice matches the PO. The PO typically contains all the necessary accounting details, which predetermines how the item is booked once received. The PO number links to the invoice, while the quantity and unit price confirm that what was ordered matches what was billed.
Emily: Should the address field also be considered for matching?
John Silverstein: The address field is hard to match but critical for capturing from a sales tax perspective. Matching addresses can be tricky because billing often happens through different entities with varying addresses, which can slow down the process. While it’s essential for tax compliance, in my experience, I don’t usually match the address due to the many nuances.
Emily: Makes sense. Should the dates on invoices be matched as well?
John Silverstein: Yes, but dates should be matched within a tolerance. An exact match isn’t always expected since invoices might be issued a day before or after the receipt of goods. There are multiple dates like order date and ship date, making it confusing. AI can help with this by identifying the appropriate dates, but it’s still important to have some flexibility when matching dates to avoid unnecessary back-and-forth.
Emily: What do you do for tax matching?
John Silverstein: Sales tax typically isn’t matched at the PO level as the PO might not include sales tax details. However, it’s crucial to capture and validate this information. If you’re tax-exempt, you want to ensure you aren’t being charged incorrectly. Even when there’s no sales tax, it’s still important to check since your organization might still be liable.
Emily: What are the potential risks of matching too many fields in the AP process?
John Silverstein: The main risk is that you’ll never achieve an exact match on all fields like descriptions, item codes, product codes, and dates due to differences between the vendor and your system. It’s crucial to only match fields that are necessary for catching fraud and discrepancies like quantities and amounts. Matching too many fields can lead to errors, confusion, and manual processing, which defeats the purpose of automation.
Emily: On the flip side, what could be the consequences of matching too few fields?
John Silverstein: Matching too few fields, like just the PO, could result in missing key details such as quantities received. It’s important to strike a balance matching enough fields to ensure accuracy without overcomplicating the process. Depending on your industry, you’ll have different rules and risks to consider, but finding the right balance is key.
Emily: How can AI play a role in optimizing the matching process?
John Silverstein: AI accelerates the process by allowing systems to read invoices and correctly match them with POs and receipts. In the past, this was a manual process, often involving paper checks. AI not only automates this process but also improves accuracy by identifying potential matches that might not be straightforward. As AI learns over time, it can even begin to match more fields that weren’t possible before, reducing errors and manual interventions.
Emily: How do you balance the need for accuracy with the need for efficiency in the AP process?
John Silverstein: It’s all about how many fields you’re matching and capturing. Accuracy is crucial because it impacts accounting, audits, and overall financial integrity. AI helps by learning and adapting over time, enabling you to strike the right balance between accuracy and efficiency. As AI continues to evolve, it will further optimize this balance by reducing manual checks and improving the precision of automated matching.
Emily: Looking ahead, how do you see the role of AI and technology evolving in the accounts payable process?
John Silverstein: AI will make AP processes much easier by taking over tasks that currently require manual effort, like data entry. The keystrokes and data entry AP clerks handle today should become minimal. AI will also improve the integration between AP and AR processes, simplifying how invoices are issued and paid. Eventually, AI will handle complex formats and requirements, transforming how organizations interact with vendors and customers. It’s exciting to think about the potential AI has to make accounts payable more efficient and less error-prone.
Emily: Thank you so much, John, for sharing your insights on such an important topic. It’s clear that the right approach to matching in accounts payable, when supported by AI, can significantly impact a company’s financial health and operational efficiency.
John Silverstein: No problem. Thank you.
